Variation in Survival and Gut Microbiome Composition of Hatchery-Grown Native Oysters at Various Locations within the Puget Sound

ABSTRACT The Olympia oyster (Ostrea lurida) of the Puget Sound suffered a dramatic population crash, but restoration efforts hope to revive this native species. One overlooked variable in the process of assessing ecosystem health is association of bacteria with marine organisms and the environments they occupy. Oyster microbiomes are known to differ significantly between species, tissue type, and the habitat in which they are found. The goals of this study were to determine the impact of field site and habitat on the oyster microbiome and to identify core oyster-associated bacteria in the Puget Sound. Olympia oysters from one parental family were deployed at four sites in the Puget Sound both inside and outside of eelgrass (Zostera marina) beds. Using 16S rRNA gene amplicon sequencing of the oyster gut, shell, and surrounding seawater and sediment, we demonstrate that gut-associated bacteria are distinct from the surrounding environment and vary by field site. Furthermore, regional differences in the gut microbiota are associated with the survival rates of oysters at each site after 2 months of field exposure. However, habitat type had no influence on microbiome diversity. Further work is needed to identify the specific bacterial dynamics that are associated with oyster physiology and survival rates. IMPORTANCE This is the first exploration of the microbial colonizers of the Olympia oyster, a native oyster species to the West Coast, which is a focus of restoration efforts. The patterns of differential microbial colonization by location reveal microscale characteristics of potential restoration sites which are not typically considered. These microbial dynamics can provide a more holistic perspective on the factors that may influence oyster performance.


Spectrum 01982-21 review
This study characterizes the microbiome of Olympia oysters after a field study at 4 location in Puget Sound. The study was designed to evaluate the effect of site on survival and microbiome composition in oysters, with the goal of informing oyster restoration. As such, it has a strong rationale and justification. The study provides a useful baseline of knowledge about differences in microbial communities in Olympia oysters between sites. The microbiome analysis methods and the sample size used (when pooling samples from 2 habitats within site) are valid for determination of differences in microbiome composition between sites.
The manuscript, however, as currently written, has somewhat overstated the conclusions and implications of the work by strongly focusing on role of microbiome on survival (as illustrated in the title). There are some issues with the experimental design that preclude any strong conclusions about a relationship between survival at a site and microbiome composition. These include: a) there was no true cage replication at each site, so the effect of site on survival could not be statistically determined; and b) No diagnosis was performed on the oysters, and the timing of mortality for each cage is not known. As such, the discussion has several areas in which the conclusions are not necessarily supported by the data. For example, there is no evidence from the presented data indicating dysbiosis at any of the oysters or sites. Regarding the role of vibrios on survival, not all vibrio spp. present in oyster gut samples are pathogenic -indeed, most vibrio spp. are non-pathogenic. Do vibrios cause disease outbreaks in Olympia oysters, or are this just due to secondary growth of bacteria due to other disease issues? Some more detailed comments: Line 30 -This conclusion about habitat type may be overstated -was there enough power in the experiment to detect differences between habitat site, just with 10 oysters in one single cage?
Line 62 -Not sure what it is meant by "as microbes are either exposed to the same environmental conditions or are…." in regards to the impact of stress on host microbiomes.
Line 70 -In addition to affecting the host though production of antibiotics, the microbiome can potentially affect the host health through a variety of mechanisms, from improving digestion and providing nutrients, detoxification, modulation of inflammation, etc. I suggest adding here some general literature from other organisms and oysters (e.g. probiotics).
Line 88 -only one cage per site -no replication at each site.
Line 162 -Sampling depth of 1920 for RPCA -why? Could you provide a rationale?
Line 174 -The sample depth of 1000 reads was used to perform the analysis with the gut samples, which is a pretty low number of reads. Authors should provide evidence from a rarefaction analysis or other analysis that this sample depth provides a true representation of the community at each site. Authors should also show as supplementary data the read depth for each oyster and site and sample type, so the reviewers can assess any potential biases due to major differences in read depth between these factors.

Results
Line 180 (and Figure 1)-The text mentions differences in survival between habitats, is this the average for all sites? If so, provide average and standard deviation, and if that difference in survival is consistent at all sites. In figure  1, the data for survival should be shown for each cage, by site and habitat, or, at the very least, the mean survival plus/minus standard deviation for the two cages at each site.
Line 200 - Figure 2A shows very similar values of Shannon index (overlapping) between biofilm and marine sediment, are these truly significant in pairwise comparisons? Please show overall stats as supplementary data.
Line 203 -Indicate in the text that this data is shown in Fig 2A (not just figure  2). Same for the following lines (indicate which of the panels within Authors should also show data on alpha and beta diversity by site for the gut samples (needed to make any arguments about dysbiosis). Figure 1 -What is the process of data curation for DO and Temp? There seems to be some dips in DO in the CL eelgrass that are not seen at any of the other sites. Are these real? Figure 2. Clarify in the figure legend that this is data is for only 3 oysters per cage. For 2A indicate significance for pairwise comparisons in the legend or in the figure. For 2B -I recommend that the authors use a combination of symbols (open and closed) to indicate the site and habitat source for each oyster., and better define in the legend what the figure is showing, which groupings are significantly different, and provide a table with the loadings for each grouping.

Conclusion
Lines 279 -280 -I would not base the choice of restoration sites based on this limited set of data. The experimental design does not allow to establish a relationship between particular taxa and survival.
Lines 363 -367 -These statements are inaccurate, are not a reflection of what is known about oyster diseases in general or disease in Olympia oysters in particular. For example, what do the authors mean that "pathogens can come from within the oyster"? Throughout -Use a consistent format for int text citations.

Reviewer #1
Reviewer #1 (Public repository details (Required)): I would suggest submission of sequencing reads to NCBI in addition to proposed repository. Data sharing plan is adequate. Reads submitted to ENA are deposited into the SRA, and so they are available on NCBI -(Project Accession: PRJEB49367) Reviewer #1 (Comments for the Author): Stats seem appropriate for the microbiome analysis, but some more detail about the results from the statistical tests should be included in the manuscript.

Tables (Supplementary tables A, B, C, D) for relevant statistical tests have been added to the supplementary data and all formulas are available in the script files of the public GitHub repository "Olympia Oyster Microbes". Most tests used to calculate significance are non-parametric tests due to the nature of the data (microbiome data uses sparse matrices which are not normally distributed).
This study characterizes the microbiome of Olympia oysters after a field study at 4 location in Puget Sound. The study was designed to evaluate the effect of site on survival and microbiome composition in oysters, with the goal of informing oyster restoration. As such, it has a strong rationale and justification. The study provides a useful baseline of knowledge about differences in microbial communities in Olympia oysters between sites. The microbiome analysis methods and the sample size used (when pooling samples from 2 habitats within site) are valid for determination of differences in microbiome composition between sites.
The manuscript, however, as currently written, has somewhat overstated the conclusions and implications of the work by strongly focusing on role of microbiome on survival (as illustrated in the title). There are some issues with the experimental design that preclude any strong conclusions about a relationship between survival at a site and microbiome composition. These include: a) there was no true cage replication at each site, so the effect of site on survival could not be statistically determined; and b) No diagnosis was performed on the oysters, and the timing of mortality for each cage is not known.
These concerns are valid, and so as not to mislead the reader, the title has been changed. We have made efforts to make it clear in the main text that these are only observed trends and we do not have the power to statistically connect the microbiome to survival (lines 386-388). These limitations have been further exemplified in the text (Lines 417-429).
As such, the discussion has several areas in which the conclusions are not necessarily supported by the data. For example, there is no evidence from the presented data indicating dysbiosis at any of the oysters or sites. Regarding the role of vibrios on survival, not all vibrio spp.present in oyster gut samples are pathogenic -indeed, most vibrio spp. are non-pathogenic. Do vibrios cause disease outbreaks in Olympia oysters, or are this just due to secondary growth of bacteria due to other disease issues?

While the shift in Vibrio composition and loss of
We have mentioned in the text that Vibrios are "a common constituent of the oyster microbiome and are generally non-pathogenic" so as not to mislead the reader (lines 346-347). While we cannot determine with confidence that the species present in Skokomish are pathogenic, the overabundance of Vibrio could suggest opportunistic or pathogenic behavior.

However, as you point out, there are no studies that identify Vibrio infections of Olympia oysters (specifically Vibrio that are harmful to the oyster rather than human Vibrio pathogens accumulating in the oysters). This caveat has been added to the discussion (lines 379-380).
Some more detailed comments: Line 30 -This conclusion about habitat type may be overstated -was there enough power in the experiment to detect differences between habitat site, just with 10 oysters in one single cage?

For these tests, there were 31 oysters from eelgrass and 27 oysters from unvegetated habitat across all the sites. There were also 12 sediment, 12 water and 12 shell biofilm samples for each habitat type. This brings the total to around 65 samples per habitat type. There was no interaction between site and habitat or sample type and habitat. For both Alpha and Beta diversity statistical tests, F was very low, and the p value was very high, so we do not expect that higher sample sizes would yield a different result.
Line 62 -Not sure what it is meant by "as microbes are either exposed to the same environmental conditions or are…." in regards to the impact of stress on host microbiomes.

Apologies, we can see that this was poorly worded, and have adjusted the sentence to make it clearer. It now says, "Environmental stress can alter diversity and composition of oyster microbiomes, either as a result of bacterial response to the changing environment, or to the host's changing gene expression" (lines 57-59). For example, the host immune response could be changing by increasing or decreasing antimicrobial activity.
Line 70 -In addition to affecting the host though production of antibiotics, the microbiome can potentially affect the host health through a variety of mechanisms, from improving digestion and providing nutrients, detoxification, modulation of inflammation, etc. I suggest adding here some general literature from other organisms and oysters (e.g. probiotics).

This is a great addition -we have added a list of bacterial contributions to their host and corresponding literature, all of which derived from invertebrate models.
Line 88 -only one cage per site -no replication at each site.
This was identified as a study constraint. After finding no differences in the microbiome between eelgrass and bare habitat, we technically have 2 cages per site.
Line 162 -Sampling depth of 1920 for RPCA -why? Could you provide a rationale?

An initial rarefaction depth of 1920 was selected because the rarefaction curve shows that Shannon alpha diversity plateaus for all sample types after ~2000 sequences. However, gut samples have much lower sequence counts than other samples, and in order to retain most of the gut samples, we must rarefy below 2000 sequences. The specific count of 1920 was chosen based on the feature counts per sample after filtering the OTU table to remove chloroplast, mitochondrial, and other reads only present 3 or fewer times. The feature count which was closest to 2000 was 1922 for PG Gut eelgrass 11. Therefore, this sample was retained in the analysis by rarefying at 1920 for the alpha diversity analysis and RPCA beta diversity analysis. All feature counts lower than this were below 1500 sequences.
Line 174 -The sample depth of 1000 reads was used to perform the analysis with the gut samples, which is a pretty low number of reads. Authors should provide evidence from a rarefaction analysis or other analysis that this sample depth provides a true representation of the community at each site. Authors should also show as supplementary data the read depth for each oyster and site and sample type, so the reviewers can assess any potential biases due to major differences in read depth between these factors.

Results
Line 180 (and Figure 1)-The text mentions differences in survival between habitats, is this the average for all sites? If so, provide average and standard deviation, and if that difference in survival is consistent at all sites. In figure  1, the data for survival should be shown for each cage, by site and habitat, or, at the very least, the mean survival plus/minus standard deviation for the two cages at each site.

Yes, this is the average for all sites. We have specified this and added the standard deviations for each habitat in the text and provided 'per cage' survival and sample sizes in the figure by dividing them between habitats at each site. The difference in survival between habitat types is not significant and varies by site, with some sites having higher survival in eelgrass (Case Inlet & Skokomish) and some sites having higher survival in the bare habitat (Port Gamble and Fidalgo Bay). We have included the p-value from a two-way t-test to make this point clearer.
Line 200 - Figure 2A shows very similar values of Shannon index (overlapping) between biofilm and marine sediment, are these truly significant in pairwise comparisons? Please show overall stats as supplementary data.

For Shannon alpha diversity group significance, all groups are significantly different from one another. The Kruskal -Wallis pairwise comparisons have been included in the supplementary data and this shows that, despite proximity in the figure, even sediment and biofilm groups vary significantly in their alpha diversity (Supplementary Figure E). We have also added significance bars in the figure 2A itself to indicate all groups are different from one another.
Line 203 -Indicate in the text that this data is shown in Fig 2A ( Lines 226 -270: Much of this information belongs in the methods section. Authors should also show data on alpha and beta diversity by site for the gut samples (needed to make any arguments about dysbiosis). Figure 4 by the RPCA PCoA plot and statistics for significant differences are reported in the text. Figure 1 -What is the process of data curation for DO and Temp? There seems to be some dips in DO in the CL eelgrass that are not seen at any of the other sites. Are these real? Fig 1B and

Conclusion
Lines 279 -280 -I would not base the choice of restoration sites based on this limited set of data. The experimental design does not allow to establish a relationship between particular taxa and survival.

The study does not claim statistical power to confirm the link between particular taxa and survival. However, the differences in survival and microbiomes, even on their own, are partial indicators of suitability for restoration.
Lines 363 -367 -These statements are inaccurate, are not a reflection of what is known about oyster diseases in general or disease in Olympia oysters in particular. For example, what do the authors mean that "pathogens can come from within the oyster"?
We apologize that the wording has confused the reader. Rather than describing oyster disease, the goal is to explain that more information about the role of the microbiome in disease is being published. We hope to rationalize some of the patterns that were seen in the data by comparing our outcomes to other studies that characterize the microbiome in response to disease or severe stress. We

Throughout -Use a consistent format for int text citations.
We have ensured that citations follow a consistent pattern.

Reviewer #2
The manuscript describes differences in the microbial community from oyster gut, sediment and seawater in relation to habitat (eelgrass vs no eelgrass), site and physicochemical parameters. The study found significant differences in oyster survival and microbiome across sites, but not between habitats. Further analysis of the oyster gut microbial community was performed to identify core bacterial taxa and link the presence of specific bacterial taxa (eg Mycoplasma, Vibrio, Synechococcus) with oyster survival rates. The results will assist in identifying suitable sites for Olympia oyster restoration and the microbiome approach may be used to assess oyster health. The manuscript is well written and makes a significant contribution to the scientific community.
Reviewer #2 (Public repository details (Required)): 16S rRNA gene sequences should be deposited in a public repository. The authors have stated "Sequence data generated in this project will be deposited in the EBI-ENA database and made 430 available through Qiita (Study ID: 12079)".

Reviewer #2 (Comments for the Author):
The authors have already highlighted limitations to this study eg lack of time points, batch effects, lack of quantitative data. One approach to deal with the lack of absolute abundance data which could be further discussed, would be to normalise the data against total 16S bacterial qPCR values (eg King WL, et al. (2021). Front Microbiol 12:723649). While this is not absolute quantification, it would allow comparisons of specific taxa abundance between samples. In addition, future work could be directed at specifically detecting bacterial groups identified as being of interest such as Mycoplasma, Vibrio and Synechococcus, for example, by qPCR, in addition to whole bacterial community analysis.

Reviewer #3
Reviewer #3 (Public repository details (Required)): Manuscript indicates files are deposited in a public repository Reviewer #3 (Comments for the Author): This manuscript investigated the bacteria community of the Olympia oyster in four locations of Puget Sound. The major finding is the bacteria community of the digestive gland of oysters differs from the surrounding seawater, sediment and oyster shell. These results are interesting to the field of oyster health and restoration, but not novel. The manuscript is well written, conclusions are strongly supported by the results with appropriate methods and statistical analysis. Limitations are identified and clearly discussed.
The manuscript could be improved if the authors could provide other metrics for oyster health, such as growth rate, condition or presence of biofouling.

Unfortunately, the length of the oysters could not be measured at the beginning of the field exposure, so we do not have growth data. Additionally, we do not have any weight measurements (of tissue or whole shell). We do have the lengths of the oysters at the end of the experiment. The lengths do vary significantly across the sites (single factor ANOVA, p = 0.006 for shell width, p = 0.038 for shell length), but we do not think this is worth reporting because we do not have the change in length, and therefore cannot make any assumptions about differences in growth across sites. We do not have qualitative metadata for biofouling, but all the "Cages were cleaned of biofouling organisms and debris every two weeks during the deployment" (lines 95-96) as a protective measure for the oysters.
I was a little confused with some of the environmental data and its interpretation due to the faulty salinity measurements from malfunctioning instruments. (32.6 for PGB, 33.0 for PGE, 31.9 for FBB, 31.7 for  SKB, and 30.8

for SKE). For sites where the Odyssey Conductivity Sensors failed, we used the mean salinity value from the adjoining site. For example, the in situ value of 31.9 for FBB was used for FBE. At CI, where Odyssey Conductivity Sensors failed at both the Eelgrass site and the Bare site, we obtained salinity data from the Washington State Department of Ecology Long-Term Marine Water Monitoring Program, which recorded a surface salinity of 29.5 in Case Inlet (station CSE001) in August 2018.
It would also be interesting if the Vibrio associated with higher mortality of oysters is a single ASV (potentially indicating an infection). I also appreciate that the authors may of decided not to speculate because of the close 16S rRNA gene sequences for the genus.

The Vibrio identified in the RPCA biplot as driving differences between sites is a single ASV. However, the songbird differentials include all ASVs from the gut samples that were identified as Vibrio at the genus level. This comprises 2 ASVs. The primary Vibrio ASV driving the separation for Skokomish does not have a singular species hit when BLAST against NCBI nucleotide database, but the top hits do compromise a list of known or suspected oyster pathogens (1-Vibrio toranzoniae, 2-Vibrio crassostreae, and 3-Vibrio kanaloae). However, we cannot statistically associate these with mortality due to a lack of power.
I am assuming the reported oxygen in mg.l was not corrected for salinity (line 132).

Lines 129-130 state that "Dissolved oxygen data were adjusted based on salinity and reported in mg*L -1 " All dissolved oxygen data were corrected for salinity using methods and values detailed above.
The increased proportion of Mycoplasma in oysters from Case Inlet and Fidalgo Bay may also be because these oysters were not feeding at the time of sampling, which might be supported by reduced proportion of Synechoccous (transient bacteria from feeding??).

This is a great point. We have adjusted the discussion to include this point before moving on to the dynamics between Mycoplasma and Vibrio.
Line 24 -biparental family? Or was it a mix of families from a single spawn.

A group of Olympia oysters originally from a North Fidalgo Bay subpopulation were maintained in a research facility in Manchester, Washington and conditioned to spawn. The spawn were raised in a common tank and oysters from this spawn were outplanted in all the field sites for this study. In the manuscript, we have included a line to indicate this: "All oysters used were from a common genetic background (a subpopulation of Fidalgo Bay oysters) and were raised in the same hatchery conditions."
Line 85 -please provide addition information about genetics of oysters. Large amount of recent research has shown that genetics influences the bacterial community.

A line was included in the methods to explain that all oysters used in this study were from the same genetic background and raised under the same conditions.
Line 107 -the amount of time that oysters were transported between sites and would this influence the bacteria community (i.e. 1 hour for site A and 4 hours for site D).

All locations were a similar distance from the lab (1.5-2 hours), so it is unlikely that this would have driven any microbial differences between the sites. This is a good point and if there were greater differences in travel time, the oysters likely would have been dissected and frozen in the field.
Line 161 -sequencing depth of 1,920. Is this not low for microbiome analysis, which is typically >10,000 reads per sample.

Sequencing depth may be considered low in comparison to other microbiome analyses. In this study, we especially had to account for the lower diversity exhibited by oyster guts. Some (not all) prior literature shows similar rarefaction for oysters/ oyster guts (Dubé, Ky, and Planes 2019; Trabal Fernandez et al 2014). We have added the rarefaction curves to the supplementary data to demonstrate that the diversity plateaus early, justifying the ability to rarefy at 1,920 for all sample types, and at 1,000 for gut samples only.
Line 178 -please provide statistical justification for increased survival. Maybe not possible with 1 replicate cage.

We ran a proportion test in R on the number of surviving oysters for each site (for both eelgrass and bare habitat included) out of the total oysters at that site, and it reported that survival was significantly different with a p value of 0.0258. However, after running a pairwise proportion test, only the difference between Port Gamble and Case Inlet is significant. We are reporting this in the text for clarification. However, as explained in the limitations of the study, this survival cannot be directly linked to the microbiome since we do not know the microbiome at the time of death. The survival data in tandem with specific bacteria in the gut helps generate hypotheses about the types of bacteria to monitor in future studies.
Line 240 -abundance or proportion of ASVs (amplicon reads).

We have tried to explain the "zeros" in a different way. If an ASV that was not detected in a sample, then its value is zero, and so the log ratio cannot be computed.
Line 334 -same as line 240.

We have decided to stick with "ratio", as this is the most accurate way to explain the comparison between the taxa.
Could the abundance of Vibrio increased in a sick oyster, and so the proportion (%) of core bacteria in the community reduced. Would performing a qPCR assay for total 16S rRNA and Vibrio 16S rRNA provide data on this point.
We agree this is the hypothesis. We have highlighted the point that core bacteria (Mycoplasma) are outweighed by the Vibrio at Skokomish. However, qPCR assays, specifically with total 16S rRNA quantification and targeted Vibrio quantification are outside the bounds of this work, as they require additional method development to maximize efficiency and reliability.
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This manuscript investigated the bacterial community of the Olympia oyster in Puget Sound. Although the research has important implication, the methods and results are not novel. Other specific comments are as follows: 1. The experimental design, especially the sampling process, has great deficiencies. For example, the Case Inlet, which served as an important control, only 3 water samples were taken (n = 2 inside eelgrass beds and n = 1 outside eelgrass) in the study. At least 3 parallels are required to meet statistical requirements. Figure F showed that the sequencing depth of some samples were insufficient. 3. The association between survival rate and microbiome has not been sufficiently analyzed and explored. 4. Mycoplasma had been found in many molluscs, such as in abalones (some was more than 80% in the diseased individual). Although the similar findings were found in this study, related causes were not analyzed and discussed in the Discussion of the manuscript. 5. Similarly, the manuscript has somewhat overstated the conclusions and implications of the work by strongly focusing on role of microbiome. Attention on the status of oysters was insufficient. It is suggested to add the physiological indicators or some key immune index of the oysters ,and also the growth rate ( or detect changes in body weight or shell length), in addition to survival rate.

Supplemental
Reviewer #5 (Comments for the Author): The manuscript entitled "Variation in survival and gut microbiome composition of hatchery grown native oysters at various locations within the Puget Sound" by Kunselman et al. investigates changes in microbial communities, characterized by 16S rRNA gene sequencing, associated with different tissues of the native Olympia oyster at various sites and habitats in the Puget Sound. The goal of this study is to determine the impact of field site and habitat on the oyster microbiome (mainly the gut) to assess ecosystem health and to inform possible restoration efforts of depleted oyster beds in the Puget Sound. Overall, the manuscript is well written, coherent, and well-presented and I enjoyed reading it. The experimental techniques and statistical analyses are appropriate. I do have some general comments and suggestions for improvement that would need to be addressed before the manuscript could be published.
General comments: 1/ Although restoration of keystone species' natural beds is crucial from an ecological, economical or societal standpoint, I am struggling a bit with the significance of this study and its contextualisation (Line 34 -39). NGS technologies and the use of microbiome have clearly been instrumental in recent years to better understand interactions between host-pathogenenvironment as well as characterizing the general health of habitats. However, the proposed justification to use metabarcoding to inform decision on site selection for restoration appears a bit "stretchy".
2/ Authors should be cautious in the way some conclusions are presented and should moderate some statement to avoid overreached findings. The experimental approach has limitations -which the authors have appropriately highlighted at the end of the discussion -that affect the significance of the results.
3/ One of the main limitations of the design, in my opinion, is the limited number of animals deployed per cage/site (n = 10). Estimating survivorship from such low number and consequently using survival as a proxy to evaluate the general health of the habitat and its adequacy for restoration purposes does not support one of the main outcomes. In addition, as noted by the authors, adding at least another time point for sampling would have greatly improve this study. 4/ The use of a reference taxon for determining ratio and therefore characterize differential abundance between site is a sound statistical approach. Have the authors considered other analyses such as Random Forest model or Pearson correlation to establish specific ASVs that can predict performances?
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